Analysis overview

This systematic review and meta-analysis evaluated the effects of NMDA receptor antagonists on locomotion in the social interaction test outcomes in animal models. Effect sizes were calculated as Hedges’ g and synthesized using multilevel random-effects models to account for dependency between multiple outcomes within experiments and studies.

Study landscape and evidence distribution

Alluvial plot

Distribution of species across NMDA receptor antagonists.
Alluvial plot showing how effect sizes are distributed across animal species and NMDA receptor antagonists.

Evidence maps

Evidence maps of experimental design characteristics.
Bubble size represents the number of effect sizes (k), and color indicates the mean Hedges’ g within each cell.

Main meta-analysis

Overall effect

## 
## Multivariate Meta-Analysis Model (k = 170; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  1.180  1.086     51     no         study_id 
## sigma^2.2  0.201  0.449    117     no  study_id/exp_id 
## 
## Test for Heterogeneity:
## Q(df = 169) = 992.023, p-val < .001
## 
## Number of estimates:   170
## Number of clusters:    51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
## 
## Model Results:
## 
## estimate     seÂą   tvalÂą     dfÂą   pvalÂą  ci.lbÂą  ci.ubÂą    
##    0.400  0.172   2.320   49.12   0.025   0.054   0.747   * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t-test and confidence interval, df: Satterthwaite approx)

Multilevel random-effects meta-analysis with robust variance estimation.

Orchard plot

Overall effect of NMDA receptor antagonists on locomotion in the social interaction test.
Orchard plot summarizing study-level pooled effects with multilevel heterogeneity.

Prediction interval for the overall effect

##    estimate      ci_lb     ci_ub     pi_lb    pi_ub
## 1 0.4000693 0.05353985 0.7465987 -1.986984 2.787122

Prediction interval for the overall effect. The 95% prediction interval reflects expected variability in the true effect size of a future study beyond sampling error.

##            Component I.....
## 1           I2_Total   83.8
## 2        I2_study_id   71.6
## 3 I2_study_id/exp_id   12.2

Multilevel heterogeneity estimates (I²).

Publication bias

Funnel plots

Funnel plot using standard error.

Funnel plot using inverse square root of total sample size.

Precision Effect Test (PET)

## 
## Multivariate Meta-Analysis Model (k = 170; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  2.719  1.649     51     no         study_id 
## sigma^2.2  0.164  0.405    117     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 168) = 939.914, p-val < .001
## 
## Number of estimates:   170
## Number of clusters:    51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 9.95) = 15.750, p-val = 0.003
## 
## Model Results:
## 
##           estimate     seÂą    tvalÂą     dfÂą   pvalÂą   ci.lbÂą   ci.ubÂą     
## intrcpt     -3.803  1.049   -3.626   18.78   0.002   -6.000   -1.606   ** 
## sqrt(vi)     7.717  1.945    3.969    9.95   0.003    3.381   12.053   ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

PET (Precision Effect Test) model with robust variance estimation. The PET model evaluates small-study bias by regressing effect size on study precision.

Precision Effect Estimate with Standard Error (PEESE)

## 
## Multivariate Meta-Analysis Model (k = 170; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  2.255  1.502     51     no         study_id 
## sigma^2.2  0.139  0.373    117     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 168) = 937.527, p-val < .001
## 
## Number of estimates:   170
## Number of clusters:    51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 6.74) = 9.524, p-val = 0.019
## 
## Model Results:
## 
##          estimate     seÂą    tvalÂą     dfÂą   pvalÂą   ci.lbÂą   ci.ubÂą    
## intrcpt    -1.227  0.548   -2.237   33.54   0.032   -2.342   -0.112   * 
## vi          5.265  1.706    3.086    6.74   0.019    1.200    9.331   * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

PEESE (Precision Effect Estimate with Standard Error) model with robust variance estimation. The PEESE model provides an alternative bias-adjusted estimate using study variance.

Time-lag bias

## 
## Multivariate Meta-Analysis Model (k = 170; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  0.976  0.988     51     no         study_id 
## sigma^2.2  0.213  0.462    117     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 168) = 911.561, p-val < .001
## 
## Number of estimates:   170
## Number of clusters:    51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 25.73) = 7.738, p-val = 0.010
## 
## Model Results:
## 
##          estimate     seÂą    tvalÂą     dfÂą   pvalÂą   ci.lbÂą   ci.ubÂą     
## intrcpt     0.569  0.172    3.300   31.13   0.002    0.217    0.920   ** 
## year_c     -0.052  0.019   -2.782   25.73   0.010   -0.090   -0.014   ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

Time-lag meta-regression model. This model tests whether effect sizes change systematically over publication time. A significant slope would indicate temporal trends such as decline or inflation of reported effects.

Time-lag bias: effect size as a function of publication year.

Moderators

Moderator analyses were conducted using multilevel meta-analytic models with robust variance estimation to examine whether effect sizes differed across experimental and biological characteristics. Orchard plots display pooled effects for each moderator level, with study-level clustering and multilevel heterogeneity taken into account.

## 
## Multivariate Meta-Analysis Model (k = 170; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  1.049  1.024     51     no         study_id 
## sigma^2.2  0.182  0.427    117     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 167) = 924.069, p-val < .001
## 
## Number of estimates:   170
## Number of clusters:    51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
## 
## Test of Moderators (coefficients 1:3):Âą
## F(df1 = 3, df2 = 14.57) = 5.409, p-val = 0.010
## 
## Model Results:
## 
##                               estimate     seÂą    tvalÂą     dfÂą   pvalÂą 
## nmda_antagonistKetamine         -0.769  0.438   -1.756    6.05   0.129  
## nmda_antagonistMK-801            0.552  0.276    2.004   23.17   0.057  
## nmda_antagonistPhencyclidine     0.610  0.263    2.321   19.86   0.031  
##                                ci.lbÂą  ci.ubÂą    
## nmda_antagonistKetamine       -1.839   0.301     
## nmda_antagonistMK-801         -0.018   1.122   . 
## nmda_antagonistPhencyclidine   0.061   1.158   * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 170; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  1.245  1.116     51     no         study_id 
## sigma^2.2  0.201  0.448    117     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 167) = 989.781, p-val < .001
## 
## Number of estimates:   170
## Number of clusters:    51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
## 
## Test of Moderators (coefficients 1:3):Âą
## F(df1 = 3, df2 = 3.14) = 1.151, p-val = 0.451
## 
## Model Results:
## 
##                   estimate     seÂą   tvalÂą     dfÂą   pvalÂą    ci.lbÂą   ci.ubÂą 
## speciesMouse         0.548  0.350   1.566    6.99   0.161    -0.280    1.375  
## speciesRat           0.356  0.200   1.783   40.23   0.082    -0.048    0.760  
## speciesZebrafish     0.977  6.211   0.157       1   0.901   -77.943   79.897  
##                     
## speciesMouse        
## speciesRat        . 
## speciesZebrafish    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 170; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  1.098  1.048     51     no         study_id 
## sigma^2.2  0.199  0.446    117     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 167) = 952.857, p-val < .001
## 
## Number of estimates:   170
## Number of clusters:    51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
## 
## Test of Moderators (coefficients 1:3):Âą
## F(df1 = 3, df2 = 22.47) = 6.504, p-val = 0.002
## 
## Model Results:
## 
##                                                   estimate     seÂą    tvalÂą 
## developmental_stage_inductionAdult                  -0.093  0.327   -0.285  
## developmental_stage_inductionJuvenile/Adolescent     0.666  0.215    3.099  
## developmental_stage_inductionUnclear                 0.762  0.224    3.401  
##                                                      dfÂą   pvalÂą   ci.lbÂą 
## developmental_stage_inductionAdult                20.72   0.778   -0.773  
## developmental_stage_inductionJuvenile/Adolescent   6.85   0.018    0.155  
## developmental_stage_inductionUnclear              19.66   0.003    0.294  
##                                                   ci.ubÂą     
## developmental_stage_inductionAdult                0.586      
## developmental_stage_inductionJuvenile/Adolescent  1.176    * 
## developmental_stage_inductionUnclear              1.230   ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 170; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  1.246  1.116     51     no         study_id 
## sigma^2.2  0.209  0.458    117     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 165) = 975.166, p-val < .001
## 
## Number of estimates:   170
## Number of clusters:    51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
## 
## Test of Moderators (coefficients 1:5):Âą
## F(df1 = 5, df2 = 0.8) = 0.178, p-val = 0.933
## 
## Model Results:
## 
##                                           estimate     seÂą    tvalÂą     dfÂą 
## nmda_administration_routeImmersion           0.977  6.231    0.157       1  
## nmda_administration_routeIntraperitoneal     0.272  0.239    1.138   25.58  
## nmda_administration_routeMinipump            0.731  0.756    0.967     1.4  
## nmda_administration_routeSubcutaneous        0.522  0.280    1.867    20.3  
## nmda_administration_routeUnclear            -0.100  0.941   -0.107       1  
##                                            pvalÂą    ci.lbÂą   ci.ubÂą    
## nmda_administration_routeImmersion        0.901   -78.201   80.155     
## nmda_administration_routeIntraperitoneal  0.266    -0.219    0.763     
## nmda_administration_routeMinipump         0.470    -4.281    5.743     
## nmda_administration_routeSubcutaneous     0.076    -0.061    1.105   . 
## nmda_administration_routeUnclear          0.932   -12.058   11.858     
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

## 
## Multivariate Meta-Analysis Model (k = 170; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  1.118  1.057     51     no         study_id 
## sigma^2.2  0.206  0.454    117     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 167) = 912.833, p-val < .001
## 
## Number of estimates:   170
## Number of clusters:    51
## Estimates per cluster: 1-12 (mean: 3.33, median: 2)
## 
## Test of Moderators (coefficients 1:3):Âą
## F(df1 = 3, df2 = 2.78) = 1.357, p-val = 0.412
## 
## Model Results:
## 
##                          estimate     seÂą   tvalÂą     dfÂą   pvalÂą   ci.lbÂą 
## nmda_scheduleAcute          0.199  0.153   1.297   21.49   0.208   -0.120  
## nmda_scheduleContinuous     0.839  0.713   1.177    1.29   0.412   -4.555  
## nmda_scheduleRepeated       0.648  0.256   2.535   14.23   0.024    0.101  
##                          ci.ubÂą    
## nmda_scheduleAcute       0.518     
## nmda_scheduleContinuous  6.233     
## nmda_scheduleRepeated    1.196   * 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

Meta-regression

Cumulative exposure

## 
## Multivariate Meta-Analysis Model (k = 166; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  1.183  1.088     49     no         study_id 
## sigma^2.2  0.218  0.466    115     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 164) = 947.249, p-val < .001
## 
## Number of estimates:   166
## Number of clusters:    49
## Estimates per cluster: 0-12 (mean: 3.25, median: 2)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 1.15) = 1.972, p-val = 0.371
## 
## Model Results:
## 
##                           estimate     seÂą    tvalÂą     dfÂą   pvalÂą   ci.lbÂą 
## intrcpt                      0.454  0.182    2.496   47.01   0.016    0.088  
## nmda_cumulative_exposure    -0.002  0.001   -1.404    1.15   0.371   -0.012  
##                           ci.ubÂą    
## intrcpt                   0.819   * 
## nmda_cumulative_exposure  0.009     
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

Meta-regression of cumulative exposure versus effect size. The regression coefficient indicates whether increasing cumulative exposure is associated with changes in effect size, suggesting a potential dose–response relationship.

Log-transformed cumulative exposure

## 
## Multivariate Meta-Analysis Model (k = 166; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  1.219  1.104     49     no         study_id 
## sigma^2.2  0.156  0.395    115     no  study_id/exp_id 
## 
## Test for Residual Heterogeneity:
## QE(df = 164) = 876.670, p-val < .001
## 
## Number of estimates:   166
## Number of clusters:    49
## Estimates per cluster: 0-12 (mean: 3.25, median: 2)
## 
## Test of Moderators (coefficient 2):Âą
## F(df1 = 1, df2 = 5.87) = 2.604, p-val = 0.159
## 
## Model Results:
## 
##                               estimate     seÂą   tvalÂą     dfÂą   pvalÂą   ci.lbÂą 
## intrcpt                          0.334  0.184   1.819   46.45   0.075   -0.035  
## log_nmda_cumulative_exposure     0.412  0.255   1.614    5.87   0.159   -0.216  
##                               ci.ubÂą    
## intrcpt                       0.704   . 
## log_nmda_cumulative_exposure  1.040     
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t/F-tests and confidence intervals, df: Satterthwaite approx)

Meta-regression of log-transformed cumulative exposure. The log-transformed model evaluates potential non-linear exposure–effect relationships and the robustness of the association.

Sensitivity analyses

Rho sensitivity

##   rho  estimate              ci
## 1 0.0 0.4963016  [0.142, 0.851]
## 2 0.3 0.4478885  [0.103, 0.792]
## 3 0.5 0.4000693  [0.062, 0.738]
## 4 0.8 0.2493791 [-0.094, 0.593]

Sensitivity of the overall effect to within-study correlation (rho). This analysis evaluates the robustness of the pooled effect size to assumptions about the correlation between multiple effect sizes within the same experiment. Each row reports the overall effect estimate (Hedges’ g) and 95% confidence interval obtained under a different assumed value of rho. Stability of estimates across rho values indicates robustness to within-study dependency assumptions.

Leave-one-study-out

##       left_out_study  estimate      ci_lb     ci_ub
## 1        becker_2004 0.3975451 0.05078782 0.7443025
## 2       corbett_1993 0.4216986 0.08043758 0.7629596
## 3       corbett_1995 0.3939563 0.04731135 0.7406013
## 4          dunn_1989 0.3992372 0.05440548 0.7440690
## 5      gacsalyi_2013 0.3863922 0.04364818 0.7291363
## 6    georgiadou_2013 0.4632651 0.14284978 0.7836804
## 7     gururajan_2010 0.3997394 0.05275272 0.7467261
## 8     gururajan_2011 0.3873823 0.04187492 0.7328897
## 9        haller_2005 0.4079994 0.06412950 0.7518693
## 10       hereta_2019 0.4222760 0.07907403 0.7654780
## 11     kaminska_2015 0.4107951 0.06619306 0.7553972
## 12        koros_2007 0.3908981 0.04458268 0.7372136
## 13      kovanyi_2016 0.4062544 0.06156190 0.7509470
## 14  lafioniatis_2016 0.4347309 0.09860036 0.7708614
## 15           li_2018 0.3819516 0.03879085 0.7251123
## 16   maaswinkel_2013 0.3869800 0.04211392 0.7318461
## 17      maehara_2011 0.4212613 0.07870589 0.7638168
## 18     matsuoka_2005 0.3639464 0.02763662 0.7002561
## 19     matsuoka_2008 0.3638407 0.02759701 0.7000845
## 20     morimoto_2002 0.4017572 0.05548640 0.7480279
## 21        neill_2016 0.4095787 0.06561074 0.7535467
## 22       peters_2017 0.4139121 0.07078581 0.7570384
## 23     podhorna_2003 0.3634735 0.02799127 0.6989557
## 24       pouzet_2002 0.3753292 0.03510382 0.7155546
## 25      pouzet_2002b 0.3810141 0.03731244 0.7247159
## 26         rung_2005 0.4039851 0.05926397 0.7487061
## 27        rung_2005b 0.3926086 0.04638087 0.7388363
## 28      salunke_2013 0.4069477 0.06228971 0.7516057
## 29    sams-dodd_1995 0.4194214 0.07683253 0.7620103
## 30    sams-dodd_1996 0.3793567 0.03171470 0.7269987
## 31    sams-dodd_1997 0.3678853 0.02795536 0.7078153
## 32    sams-dodd_1998 0.3491921 0.02346068 0.6749235
## 33   sams-dodd_1998b 0.3760975 0.03478288 0.7174120
## 34   sams-dodd_1998c 0.3756845 0.03305872 0.7183102
## 35   sams-dodd_1998d 0.3756334 0.03367703 0.7175898
## 36    sams-dodd_2004 0.4073744 0.06303531 0.7517134
## 37        satow_2009 0.4273704 0.08626883 0.7684719
## 38       savage_2011 0.4688266 0.15195277 0.7857004
## 39   savolainen_2018 0.4094442 0.06481252 0.7540760
## 40    silvestre_1997 0.4076892 0.06402625 0.7513522
## 41    sukhotina_1998 0.4068999 0.06206553 0.7517342
## 42       tanaka_2003 0.3572838 0.02648715 0.6880805
## 43       tanaka_2019 0.3922819 0.04716314 0.7374006
## 44      tarland_2017 0.4128575 0.06959514 0.7561199
## 45      tarland_2018 0.4137049 0.07060884 0.7568009
## 46 trevlopoulou_2015 0.4401257 0.10604559 0.7742059
## 47  vijeepallam_2016 0.3836242 0.04036572 0.7268826
## 48         wass_2009 0.4054842 0.06157279 0.7493957
## 49         yeap_2020 0.3834551 0.03958427 0.7273260
## 50          zou_2008 0.4151293 0.07181974 0.7584388
## 51        zoupa_2019 0.4372366 0.10180206 0.7726712

Leave-one-study-out analysis. Each row reports the pooled effect size (Hedges’ g) and 95% confidence interval obtained after excluding one study at a time from the meta-analysis. This analysis evaluates the influence of individual studies on the overall estimate; substantial changes after removal of a study would indicate disproportionate influence.

Excluding high risk of bias

## 
## Multivariate Meta-Analysis Model (k = 96; method: REML)
## 
## Variance Components:
## 
##            estim   sqrt  nlvls  fixed           factor 
## sigma^2.1  1.030  1.015     26     no         study_id 
## sigma^2.2  0.317  0.563     66     no  study_id/exp_id 
## 
## Test for Heterogeneity:
## Q(df = 95) = 579.671, p-val < .001
## 
## Number of estimates:   96
## Number of clusters:    26
## Estimates per cluster: 0-12 (mean: 1.88, median: 1)
## 
## Model Results:
## 
## estimate     seÂą   tvalÂą     dfÂą   pvalÂą  ci.lbÂą  ci.ubÂą     
##    0.778  0.231   3.365   24.36   0.003   0.301   1.255   ** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 1) results based on cluster-robust inference (var-cov estimator: CR2,
##    approx t-test and confidence interval, df: Satterthwaite approx)

Overall effect excluding high risk-of-bias studies. This sensitivity analysis re-estimates the overall meta-analytic effect after excluding studies classified as having high risk of bias. The purpose of this analysis is to assess whether the pooled effect estimate is robust to the exclusion of potentially biased evidence.

Annex: Individual effect sizes included in the meta-analysis

Calculated effect sizes

## 
##                 study effect_id nmda_antagonist hedges_g  ci_lb  ci_ub 
## 1      Gururajan 2011        35          MK-801    2.019  0.992  3.046 
## 2      Gururajan 2011        39          MK-801    2.040  0.959  3.121 
## 3      Gururajan 2011        43          MK-801    1.940  0.877  3.003 
## 4      Gururajan 2011        36          MK-801    0.462 -0.385  1.308 
## 5      Gururajan 2011        40          MK-801    0.467 -0.421  1.355 
## 6      Gururajan 2011        44          MK-801    0.468 -0.421  1.356 
## 7             Li 2018        53          MK-801    1.330  0.377  2.284 
## 8       Podhorna 2003       109   Phencyclidine    1.935  0.956  2.914 
## 9       Podhorna 2003       110   Phencyclidine    3.720  2.391  5.050 
## 10      Podhorna 2003       111   Phencyclidine    4.408  2.920  5.896 
## 11       Salunke 2013       119          MK-801   -0.419 -2.036  1.199 
## 12       Salunke 2013       125          MK-801    0.181 -1.422  1.785 
## 13       Salunke 2013       120          MK-801   -0.246 -1.853  1.360 
## 14       Salunke 2013       121          MK-801    0.278 -1.330  1.886 
## 15     Sams-Dodd 1997       128   Phencyclidine    3.133  1.939  4.327 
## 16     Sams-Dodd 1997       130   Phencyclidine    1.792  0.845  2.739 
## 17     Sams-Dodd 1997       132   Phencyclidine    0.739 -0.088  1.566 
## 18     Sams-Dodd 1997       134   Phencyclidine    2.140  1.136  3.143 
## 19     Sams-Dodd 1997       136   Phencyclidine    1.794  0.847  2.742 
## 20     Sams-Dodd 1997       138   Phencyclidine    2.203  1.189  3.218 
## 21     Sams-Dodd 1997       140   Phencyclidine    2.044  1.057  3.032 
## 22     Sams-Dodd 1997       142   Phencyclidine    1.134  0.272  1.996 
## 23     Sams-Dodd 1997       144   Phencyclidine    1.316  0.434  2.199 
## 24     Sams-Dodd 1997       146   Phencyclidine    1.782  0.836  2.727 
## 25     Sams-Dodd 1998       148   Phencyclidine    5.102  3.452  6.752 
## 26     Sams-Dodd 1998       150   Phencyclidine    2.640  1.545  3.734 
## 27     Sams-Dodd 1998       152   Phencyclidine    2.740  1.626  3.855 
## 28     Sams-Dodd 1998       154   Phencyclidine    1.878  0.917  2.838 
## 29   Sams-Dodd 1998 b       159   Phencyclidine    2.930  1.600  4.260 
## 30   Sams-Dodd 1998 b       160   Phencyclidine    4.287  2.609  5.965 
## 31   Sams-Dodd 1998 b       161   Phencyclidine    7.032  4.556  9.507 
## 32   Sams-Dodd 1998 b       162   Phencyclidine    1.670  0.597  2.743 
## 33   Sams-Dodd 1998 c       164   Phencyclidine    1.097  0.239  1.956 
## 34   Sams-Dodd 1998 c       166   Phencyclidine    1.607  0.687  2.527 
## 35   Sams-Dodd 1998 c       168   Phencyclidine    1.974  0.998  2.950 
## 36   Sams-Dodd 1998 c       170   Phencyclidine    1.265  0.388  2.141 
## 37    Savolainen 2018       171   Phencyclidine   -0.062 -0.803  0.679 
## 38    Savolainen 2018       172   Phencyclidine   -0.159 -0.901  0.583 
## 39        Tanaka 2019       200          MK-801    0.731 -0.034  1.496 
## 40       Tarland 2018       205   Phencyclidine   -0.388 -1.445  0.670 
## 41         Zoupa 2019       215        Ketamine   -1.602 -2.729 -0.476 
## 42     Gururajan 2010       248          MK-801    0.122 -0.572  0.816 
## 43     Gururajan 2010       252          MK-801   -0.121 -0.837  0.595 
## 44     Gururajan 2010       258          MK-801   -0.116 -0.833  0.600 
## 45     Gururajan 2010       262          MK-801    1.829  1.004  2.654 
## 46     Gururajan 2010       249          MK-801   -0.338 -1.036  0.359 
## 47     Gururajan 2010       255          MK-801    0.035 -0.680  0.751 
## 48     Gururajan 2010       259          MK-801    0.028 -0.688  0.744 
## 49     Gururajan 2010       263          MK-801    1.050  0.311  1.789 
## 50         Koros 2007       284          MK-801    0.948 -0.246  2.141 
## 51         Koros 2007       285          MK-801    2.311  0.850  3.772 
## 52         Koros 2007       286          MK-801    1.763  0.429  3.096 
## 53         Koros 2007       287          MK-801    3.314  1.571  5.057 
## 54         Koros 2007       276   Phencyclidine    1.900  0.787  3.014 
## 55         Koros 2007       277   Phencyclidine    1.051  0.065  2.037 
## 56         Koros 2007       292        Ketamine    0.576 -0.579  1.731 
## 57         Koros 2007       278   Phencyclidine    0.353 -0.578  1.284 
## 58         Koros 2007       293        Ketamine   -1.060 -2.269  0.148 
## 59         Koros 2007       279   Phencyclidine    1.090  0.100  2.080 
## 60         Koros 2007       294        Ketamine   -1.980 -3.361 -0.599 
## 61         Koros 2007       295        Ketamine   -4.001 -5.961 -2.040 
## 62       Kovanyi 2016       300   Phencyclidine    1.397  0.420  2.375 
## 63       Kovanyi 2016       301   Phencyclidine   -1.230 -2.185 -0.274 
## 64        Pouzet 2002       323   Phencyclidine    1.941  0.568  3.313 
## 65      Pouzet 2002 b       325   Phencyclidine    2.279  0.826  3.733 
## 66      Pouzet 2002 b       327   Phencyclidine    0.549 -0.603  1.702 
## 67        Savage 2011       348   Phencyclidine   -3.577 -5.028 -2.126 
## 68      Kaminska 2015       423          MK-801    0.318 -0.821  1.457 
## 69      Kaminska 2015       426          MK-801   -0.651 -1.812  0.510 
## 70       Maehara 2011       432          MK-801   -0.999 -2.009  0.011 
## 71       Maehara 2011       434          MK-801   -0.204 -1.130  0.722 
## 72     Sukhotina 1998       475          MK-801   -0.312 -1.194  0.570 
## 73     Sukhotina 1998       476          MK-801   -0.178 -1.056  0.700 
## 74     Sukhotina 1998       477          MK-801    0.531 -0.361  1.423 
## 75  Trevlopoulou 2015       482        Ketamine   -1.765 -2.920 -0.610 
## 76           Zou 2008       520          MK-801   -0.403 -1.211  0.405 
## 77          Dunn 1989       569          MK-801    0.132 -1.000  1.265 
## 78          Dunn 1989       570          MK-801    0.653 -0.508  1.815 
## 79      Gacsalyi 2013       573   Phencyclidine    1.246 -0.269  2.760 
## 80        Haller 2005       579   Phencyclidine   -1.075 -2.401  0.251 
## 81        Haller 2005       580   Phencyclidine    0.753 -0.530  2.036 
## 82   Lafioniatis 2016       593        Ketamine   -1.602 -2.902 -0.301 
## 83    Maaswinkel 2013       607          MK-801    0.742  0.101  1.382 
## 84    Maaswinkel 2013       608          MK-801    1.011  0.352  1.669 
## 85    Maaswinkel 2013       609          MK-801    2.800  1.916  3.683 
## 86      Matsuoka 2008       611          MK-801    2.298  1.569  3.027 
## 87         Neill 2016       620   Phencyclidine   -0.161 -1.142  0.821 
## 88        Peters 2017       624   Phencyclidine   -0.391 -1.415  0.633 
## 89     Sams-Dodd 1996       629   Phencyclidine   -1.231 -2.103 -0.358 
## 90     Sams-Dodd 1996       635          MK-801    0.527 -0.287  1.341 
## 91     Sams-Dodd 1996       636          MK-801   -0.452 -1.263  0.358 
## 92     Sams-Dodd 1996       637          MK-801    1.275  0.398  2.153 
## 93     Sams-Dodd 1996       638          MK-801    3.868  2.512  5.223 
## 94     Sams-Dodd 1996       639          MK-801    4.030  2.637  5.423 
## 95     Sams-Dodd 1996       641   Phencyclidine    1.739  0.800  2.678 
## 96     Sams-Dodd 1996       645   Phencyclidine    0.914  0.073  1.755 
## 97     Sams-Dodd 1996       643   Phencyclidine    1.834  0.880  2.788 
## 98     Sams-Dodd 1996       647   Phencyclidine    1.916  0.949  2.882 
## 99   Sams-Dodd 1998 d       648   Phencyclidine    1.837  0.883  2.791 
## 100  Sams-Dodd 1998 d       650   Phencyclidine    1.517  0.609  2.425 
## 101  Sams-Dodd 1998 d       652   Phencyclidine    1.824  0.478  3.171 
## 102  Sams-Dodd 1998 d       654   Phencyclidine    1.925  0.957  2.893 
## 103  Sams-Dodd 1998 d       656   Phencyclidine    1.123  0.262  1.984 
## 104  Sams-Dodd 1998 d       658   Phencyclidine    1.676  0.746  2.606 
## 105  Sams-Dodd 1998 d       660   Phencyclidine    1.119  0.259  1.980 
## 106  Sams-Dodd 1998 d       662   Phencyclidine    1.182 -0.045  2.408 
## 107  Vijeepallam 2016       690        Ketamine    1.271  0.196  2.345 
## 108       Becker 2004       712        Ketamine    0.761 -0.254  1.776 
## 109       Becker 2004       715        Ketamine    0.785 -0.174  1.743 
## 110       Becker 2004       718        Ketamine    0.679 -0.277  1.634 
## 111       Becker 2004       721        Ketamine    1.041  0.051  2.031 
## 112       Becker 2004       724        Ketamine    1.172  0.167  2.177 
## 113       Becker 2004       727        Ketamine    0.330 -0.628  1.289 
## 114       Becker 2004       700        Ketamine    0.432 -0.414  1.277 
## 115       Becker 2004       703        Ketamine    0.526 -0.414  1.466 
## 116       Becker 2004       706        Ketamine   -0.348 -1.211  0.515 
## 117       Becker 2004       709        Ketamine    0.546 -0.395  1.487 
## 118      Corbett 1993       741          MK-801   -0.948 -2.142  0.245 
## 119      Corbett 1993       742          MK-801   -0.631 -1.791  0.528 
## 120   Georgiadou 2013       749        Ketamine   -3.430 -4.970 -1.889 
## 121         Rung 2005       819          MK-801   -0.598 -1.755  0.558 
## 122         Rung 2005       820          MK-801   -0.517 -1.668  0.633 
## 123         Rung 2005       821          MK-801    1.103 -0.112  2.317 
## 124         Rung 2005       822          MK-801    0.958 -0.237  2.153 
## 125        Satow 2009       824          MK-801   -1.506 -2.788 -0.224 
## 126        Satow 2009       826          MK-801   -0.391 -1.113  0.332 
## 127        Satow 2009       828          MK-801   -0.713 -1.880  0.454 
## 128      Tarland 2017       835   Phencyclidine   -0.344 -1.399  0.712 
## 129      Corbett 1995       879   Phencyclidine   -0.490 -1.638  0.659 
## 130      Corbett 1995       880   Phencyclidine    0.845 -0.336  2.026 
## 131      Corbett 1995       883   Phencyclidine    1.095 -0.119  2.308 
## 132      Corbett 1995       885   Phencyclidine    0.743 -0.427  1.913 
## 133      Corbett 1995       887   Phencyclidine    1.343  0.090  2.595 
## 134      Corbett 1995       889   Phencyclidine    0.102 -1.030  1.235 
## 135      Corbett 1995       891   Phencyclidine   -0.105 -1.237  1.028 
## 136      Corbett 1995       893   Phencyclidine    1.381  0.122  2.640 
## 137      Corbett 1995       895   Phencyclidine    0.487 -0.661  1.636 
## 138      Corbett 1995       881   Phencyclidine    2.092  0.684  3.499 
## 139       Hereta 2019       970          MK-801   -0.372 -1.514  0.769 
## 140       Hereta 2019       973          MK-801   -0.512 -1.662  0.638 
## 141       Hereta 2019       976          MK-801   -0.184 -1.318  0.950 
## 142       Hereta 2019       979          MK-801   -0.393 -1.535  0.750 
## 143       Hereta 2019       981          MK-801   -0.960 -2.155  0.235 
## 144     Matsuoka 2005      1007          MK-801    2.291  1.563  3.019 
## 145     Morimoto 2002      1012          MK-801   -0.870 -2.167  0.427 
## 146     Morimoto 2002      1014          MK-801    0.753 -0.530  2.035 
## 147     Morimoto 2002      1017          MK-801   -0.029 -1.269  1.210 
## 148     Morimoto 2002      1019          MK-801    1.172 -0.170  2.513 
## 149       Rung 2005 b      1058          MK-801    1.076  0.087  2.064 
## 150       Rung 2005 b      1060          MK-801    0.730 -0.438  1.899 
## 151       Rung 2005 b      1062          MK-801    0.600 -0.668  1.867 
## 152       Rung 2005 b      1064          MK-801    0.478 -0.301  1.258 
## 153    Sams-Dodd 1995      1083   Phencyclidine   -0.038 -0.962  0.886 
## 154    Sams-Dodd 1995      1084   Phencyclidine   -0.335 -1.266  0.595 
## 155    Sams-Dodd 1995      1085   Phencyclidine    0.080 -0.844  1.005 
## 156    Sams-Dodd 1995      1086   Phencyclidine    0.550 -0.391  1.492 
## 157    Sams-Dodd 1995      1087   Phencyclidine    1.594  0.533  2.655 
## 158    Sams-Dodd 1995      1088   Phencyclidine    2.439  1.219  3.659 
## 159    Sams-Dodd 1995      1089   Phencyclidine    3.206  1.810  4.603 
## 160    Sams-Dodd 1995      1090   Phencyclidine    3.876  2.308  5.443 
## 161    Sams-Dodd 1995      1091   Phencyclidine    0.361 -0.571  1.292 
## 162    Sams-Dodd 2004      1098          MK-801    2.820  1.222  4.418 
## 163    Sams-Dodd 2004      1096          MK-801   -0.223 -1.358  0.912 
## 164    Sams-Dodd 2004      1099          MK-801   -0.641 -1.801  0.520 
## 165    Sams-Dodd 2004      1097          MK-801    1.118 -0.099  2.335 
## 166    Silvestre 1997      1102        Ketamine   -0.101 -1.341  1.140 
## 167       Tanaka 2003      1107          MK-801    4.709  3.155  6.263 
## 168       Tanaka 2003      1106   Phencyclidine    2.596  1.510  3.682 
## 169         Wass 2009      1122   Phencyclidine    0.024 -1.215  1.264 
## 170         Yeap 2020      1132          MK-801    1.198  0.425  1.972

Individual effect sizes included in the meta-analysis. This table lists all calculated Hedges’ g values and corresponding confidence intervals used in the analyses.

Session info

## R version 4.3.1 (2023-06-16 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 11 x64 (build 26100)
## 
## Matrix products: default
## 
## 
## locale:
## [1] LC_COLLATE=Portuguese_Brazil.utf8  LC_CTYPE=Portuguese_Brazil.utf8   
## [3] LC_MONETARY=Portuguese_Brazil.utf8 LC_NUMERIC=C                      
## [5] LC_TIME=Portuguese_Brazil.utf8    
## 
## time zone: America/Sao_Paulo
## tzcode source: internal
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] RColorBrewer_1.1-3  scales_1.4.0        stringr_1.5.1      
##  [4] forcats_1.0.1       ggalluvial_0.12.5   tidyr_1.3.1        
##  [7] ggplot2_4.0.0       orchaRd_2.1.3       clubSandwich_0.6.1 
## [10] metafor_4.8-0       numDeriv_2016.8-1.1 metadat_1.2-0      
## [13] Matrix_1.6-5        dplyr_1.1.4         readxl_1.4.5       
## 
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.6       beeswarm_0.4.0     xfun_0.52          bslib_0.9.0       
##  [5] lattice_0.22-6     mathjaxr_1.6-0     vctrs_0.6.5        tools_4.3.1       
##  [9] generics_0.1.4     sandwich_3.1-1     tibble_3.2.1       pkgconfig_2.0.3   
## [13] S7_0.2.0           lifecycle_1.0.4    compiler_4.3.1     farver_2.1.2      
## [17] textshaping_1.0.0  prettydoc_0.4.1    codetools_0.2-20   vipor_0.4.7       
## [21] htmltools_0.5.8.1  sass_0.4.9         yaml_2.3.10        pillar_1.11.1     
## [25] jquerylib_0.1.4    MASS_7.3-60.0.1    cachem_1.1.0       multcomp_1.4-28   
## [29] nlme_3.1-164       tidyselect_1.2.1   digest_0.6.35      mvtnorm_1.3-3     
## [33] stringi_1.8.7      purrr_1.0.2        labeling_0.4.3     splines_4.3.1     
## [37] latex2exp_0.9.6    fastmap_1.2.0      grid_4.3.1         cli_3.6.2         
## [41] magrittr_2.0.3     survival_3.5-8     TH.data_1.1-4      withr_3.0.2       
## [45] ggbeeswarm_0.7.2   estimability_1.5.1 rmarkdown_2.30     emmeans_1.11.2-8  
## [49] cellranger_1.1.0   ragg_1.3.3         zoo_1.8-13         evaluate_1.0.5    
## [53] knitr_1.50         rlang_1.1.5        xtable_1.8-4       glue_1.8.0        
## [57] rstudioapi_0.17.1  jsonlite_2.0.0     R6_2.6.1           systemfonts_1.2.2